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AI-Powered Inspection: A Computer Vision System for Efficient Defects Detection in Underground Infrastructures
Full text linkUndetected defects in culverts and sewer pipes pose significant risks to public safety, leading to infrastructure collapses, flooding, and transportation disruptions. Traditional manual inspections are time-consuming, costly, and prone to human error, while existing automated methods struggle with occlusions, irregular defect shapes, class imbalances, and high computational demands. To address these challenges, this dissertation develops advanced semantic segmentation systems that automate defect detection, significantly improving efficiency and accuracy.
This research introduces a series of innovative models designed to overcome these challenges in underground infrastructure inspection. Using dual-attentive mechanisms, sparsely connected blocks, and depth-separable convolutions, these models improve segmentation performance and effectively handle data imbalances and variations in object characteristics. A key advancement is the Asymmetric Network, which optimizes the traditional encoder-decoder architecture by employing a more efficient decoder for upsampling and reconstruction. This approach reduces model complexity and computational costs while maintaining high accuracy. As a result, the proposed system accelerates both training and inference, reducing inspection time by up to 80\% and generating significant cost savings, making it ideal for resource-constrained environments.
This dissertation lays the groundwork for future research in adapting deep learning models to real-time inspection scenarios, integrating multi-modal data sources, and improving model generalization across various infrastructure types. At the same time, it delivers a practical, high-performing solution for automated infrastructure inspection, advancing defect detection and offering real-world value for municipalities, engineers, maintenance teams, and public works departments
Oral History Interview with Ben Zucker (Part 1)
No full textBen Zucker is the co-director of Step Up Louisiana, an economic justice organization based in New Orleans. He grew up in a family of union organizers, with both of his parents involved in labor activism. Zucker was exposed to this work from a young age and continued his involvement in social justice movements as a student at Tulane University, where he supported campus workers\u27 efforts to unionize. After graduating, Zucker worked on the Fight for 15 campaign, organizing fast food workers across the country, before returning to New Orleans to co-found Step Up Louisiana.https://scholarworks.uno.edu/ejrloh/1003/thumbnail.jp
Oral History Interview with Lloyd Robinson
No full textMr. Lloyd Robinson Jr. was born in New Orleans, Louisiana, on June 13, 1952. He was raised in a working-class family with a background in skilled trades. He experienced the integration of public schools at Abramson High School in the late 1960s. After briefly studying at Xavier University, he entered an apprenticeship program and became a pipefitter with Local 60, a career he pursued for many years, even working internationally in Algeria. Mr. Robinson was a key figure in the founding of the People\u27s Institute for Survival and Beyond, a nationally recognized anti-racism organization, and served as the president of its board. His expertise lies at the intersection of labor unionism, grassroots community organizing, and anti-racism analysis.https://scholarworks.uno.edu/ejrloh/1019/thumbnail.jp
